2022
DOI: 10.3390/ma15030823
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Method of Using the Correlation between the Surface Roughness of Metallic Materials and the Sound Generated during the Controlled Machining Process

Abstract: The article aims to use the generated sound as operational information needed for adaptive control of the metalworking process and early monitoring and diagnosis of the condition of the machined materials using a newly introduced surface roughness quality index due to the sound-controlled machining process. The object of the measurement was correlation between the sound intensity generated during cutting and the material parameters of the machined surface, i.e., the roughness of the machined surface and the de… Show more

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Cited by 7 publications
(2 citation statements)
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“…In the case of FDM-PLA printing technology, the most widespread method-material combination currently used, according to the coefficient of friction, the printing temperature has a non-linear influence, obtaining an optimal value for temperatures between 210 and 220 • C depending on the type of material [15]. This value can be correlated with an optimal level of finishing for the surface [16,17]. Another particularly important and not sufficiently well-documented aspect up to this point is represented by wear resistance.…”
Section: Introductionmentioning
confidence: 99%
“…In the case of FDM-PLA printing technology, the most widespread method-material combination currently used, according to the coefficient of friction, the printing temperature has a non-linear influence, obtaining an optimal value for temperatures between 210 and 220 • C depending on the type of material [15]. This value can be correlated with an optimal level of finishing for the surface [16,17]. Another particularly important and not sufficiently well-documented aspect up to this point is represented by wear resistance.…”
Section: Introductionmentioning
confidence: 99%
“…Murat et al [9] confirmed the high precision of the analysis method using AE signals for drill wear level classification from sharp to completely worn drill. Nahornyi et al [10] proposed using the generated sound during machining as the operational information needed for the adaptive control of the metalworking process and also for early monitoring and diagnosis of the condition of the machined materials. Sio-Sever et al [11] presented a prototype of a system for estimating the milling parameters from an AE signal using AI procedures.…”
Section: Introductionmentioning
confidence: 99%